Mercurial
annotate dictation/main.py @ 279:b3b547563ec7
Add Google connector service and agent wiki
Implement the C/Seobeo Google Drive and Gmail connector with encrypted OAuth storage, Zenbu authentication, browser testing, AI tool discovery, chunked HTTP decoding, and Bazel coverage. Consolidate repository guidance into progressive wiki documentation and enforce arena-first allocation for new first-party C code.
Co-authored-by: Copilot <[email protected]>
Copilot-Session: 84c338fd-0939-4bb3-b7f3-1062eb213e5d
| author | MrJuneJune <me@mrjunejune.com> |
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| date | Mon, 17 Aug 2026 22:22:36 -0700 |
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1 from __future__ import annotations |
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2 |
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3 import argparse |
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4 import asyncio |
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5 import json |
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6 import os |
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7 from pathlib import Path |
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8 import sys |
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9 |
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10 from dictation.config import ( |
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11 DictationConfig, |
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12 MODEL_REPOSITORY, |
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13 MODEL_REVISION, |
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14 ) |
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15 |
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16 |
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17 def download_model(config: DictationConfig) -> None: |
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18 from huggingface_hub import snapshot_download |
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19 |
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20 config.model_dir.mkdir(parents=True, exist_ok=True) |
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21 snapshot_download( |
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22 repo_id=MODEL_REPOSITORY, |
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23 revision=MODEL_REVISION, |
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24 local_dir=config.model_dir, |
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25 allow_patterns=[ |
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26 "config.json", |
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27 "model.bin", |
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28 "tokenizer.json", |
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29 "vocabulary.txt", |
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30 ], |
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31 ) |
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32 marker = config.model_dir / ".model-revision" |
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33 marker.write_text(f"{MODEL_REPOSITORY}@{MODEL_REVISION}\n", encoding="ascii") |
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34 print(f"Model ready: {config.model_dir}") |
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35 |
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36 |
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37 def preflight(config: DictationConfig) -> None: |
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38 import ctranslate2 |
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39 |
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40 compute_types = sorted(ctranslate2.get_supported_compute_types("cuda")) |
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41 if config.compute_type not in compute_types: |
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42 raise RuntimeError( |
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43 f"{config.compute_type} is unsupported on CUDA; " |
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44 f"available: {', '.join(compute_types)}" |
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45 ) |
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46 result = { |
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47 "cudaDeviceCount": ctranslate2.get_cuda_device_count(), |
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48 "computeTypes": compute_types, |
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49 "selectedComputeType": config.compute_type, |
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50 "modelDir": str(config.model_dir), |
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51 "modelPresent": (config.model_dir / "model.bin").is_file(), |
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52 } |
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53 if result["cudaDeviceCount"] < 1: |
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54 raise RuntimeError("CTranslate2 did not detect a CUDA device") |
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55 print(json.dumps(result, indent=2)) |
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56 |
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57 |
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58 async def transcribe_file(config: DictationConfig, path: Path) -> None: |
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59 from dictation.transcriber import FasterWhisperTranscriber |
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60 |
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61 transcriber = FasterWhisperTranscriber( |
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62 config.model_dir, |
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63 config.compute_type, |
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64 ) |
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65 try: |
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66 from av import open as av_open |
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67 from av.audio.resampler import AudioResampler |
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68 import numpy as np |
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69 |
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70 samples = [] |
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71 resampler = AudioResampler(format="s16", layout="mono", rate=16000) |
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72 with av_open(str(path)) as container: |
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73 for frame in container.decode(audio=0): |
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74 for converted in resampler.resample(frame): |
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75 samples.append(converted.to_ndarray().reshape(-1)) |
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76 if not samples: |
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77 raise RuntimeError("Audio file contains no decodable samples") |
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78 audio = np.concatenate(samples).astype(np.float32) / 32768.0 |
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79 result = await transcriber.transcribe(audio, final=True) |
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80 print( |
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81 json.dumps( |
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82 { |
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83 "text": result.text, |
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84 "language": result.language, |
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85 "probability": result.probability, |
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86 }, |
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87 ensure_ascii=False, |
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88 ) |
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89 ) |
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90 finally: |
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91 transcriber.close() |
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92 |
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93 |
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94 def main() -> None: |
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95 parser = argparse.ArgumentParser() |
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96 parser.add_argument( |
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97 "command", |
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98 choices=["server", "preflight", "download_model", "transcribe"], |
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99 ) |
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100 parser.add_argument("path", nargs="?") |
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101 args = parser.parse_args() |
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102 try: |
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103 config = DictationConfig.from_environment() |
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104 if args.command == "download_model": |
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105 download_model(config) |
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106 elif args.command == "preflight": |
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107 preflight(config) |
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108 elif args.command == "transcribe": |
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109 if not args.path: |
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110 parser.error("transcribe requires an audio file path") |
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111 asyncio.run(transcribe_file(config, Path(args.path))) |
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112 else: |
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113 import uvicorn |
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114 from dictation.server import create_app |
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115 |
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116 uvicorn.run( |
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117 create_app(config), |
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118 host=config.host, |
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119 port=config.port, |
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120 access_log=False, |
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121 ) |
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122 except Exception as error: |
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123 print(f"dictation: {error}", file=sys.stderr) |
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124 raise SystemExit(1) from error |
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125 |
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126 |
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127 if __name__ == "__main__": |
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128 main() |